Arid
DOI10.3390/rs70404565
Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations
Zandler, Harald1; Brenning, Alexander2,3; Samimi, Cyrus1,4
通讯作者Zandler, Harald
来源期刊REMOTE SENSING
ISSN2072-4292
出版年2015
卷号7期号:4页码:4565-4580
英文摘要

In spite of considerable efforts to monitor global vegetation, biomass quantification in drylands is still a major challenge due to low spectral resolution and considerable background effects. Hence, this study examines the potential of the space-borne hyperspectral Hyperion sensor compared to the multispectral Landsat OLI sensor in predicting dwarf shrub biomass in an arid region characterized by challenging conditions for satellite-based analysis: The Eastern Pamirs of Tajikistan. We calculated vegetation indices for all available wavelengths of both sensors, correlated these indices with field-mapped biomass while considering the multiple comparison problem, and assessed the predictive performance of single-variable linear models constructed with data from each of the sensors. Results showed an increased performance of the hyperspectral sensor and the particular suitability of indices capturing the short-wave infrared spectral region in dwarf shrub biomass prediction. Performance was considerably poorer in the area with less vegetation cover. Furthermore, spatial transferability of vegetation indices was not feasible in this region, underlining the importance of repeated model building. This study indicates that upcoming space-borne hyperspectral sensors increase the performance of biomass prediction in the world’s arid environments.


类型Article
语种英语
国家Germany ; Canada
收录类别SCI-E
WOS记录号WOS:000354789300052
WOS关键词VEGETATION INDEXES ; AVIRIS DATA ; INFRARED REFLECTANCE ; SEASONAL DYNAMICS ; EO-1 HYPERION ; CROP RESIDUE ; DISCRIMINATION ; IMAGERY ; SOIL ; SENSITIVITY
WOS类目Remote Sensing
WOS研究方向Remote Sensing
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/190151
作者单位1.Univ Bayreuth, Dept Geog, D-95440 Bayreuth, Germany;
2.Univ Jena, Dept Geog, D-07743 Jena, Germany;
3.Univ Waterloo, Dept Geog & Environm Management, Waterloo, ON N2L 3G1, Canada;
4.BayCEER, Bayreuth Ctr Ecol & Environm Res, D-95440 Bayreuth, Germany
推荐引用方式
GB/T 7714
Zandler, Harald,Brenning, Alexander,Samimi, Cyrus. Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations[J],2015,7(4):4565-4580.
APA Zandler, Harald,Brenning, Alexander,&Samimi, Cyrus.(2015).Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations.REMOTE SENSING,7(4),4565-4580.
MLA Zandler, Harald,et al."Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations".REMOTE SENSING 7.4(2015):4565-4580.
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